Imaging device for producing high resolution images using subpixel shifts and method of using same

ABSTRACT

An imaging device for producing a high resolution image of a target with an imaging sensor and a method using the same is provided. The method is comprised of the steps of: determining, from the target size, resolution requirements of the image to be produced; capturing multiple individual low resolution images of the target, a minimum number of individual images captured being based upon the resolution requirements determined in the determining resolution requirements step; moving the OIS module to specific positions between the capturing of the individual low resolution images in the capturing multiple low resolution images step, the specific positions being based upon the resolution requirements in the determining resolution requirements step; and processing the multiple low resolution images to produce a high resolution image.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims the benefit of U.S. patent applicationSer. No. 15/064,637 for An Imaging Device for Producing High ResolutionImages Using Subpixel Shifts and Method of Using Same filed Mar. 9,2016, now U.S. Pat. No. 9,674,430. Each of the foregoing patentapplication and patent is hereby incorporated by reference in itsentirety.

FIELD OF THE INVENTION

The present invention relates to image-based sensing and in particularto using an imaging sensor to produce high resolution images.

BACKGROUND

Generally speaking image-based data entry, including optical characterrecognition and barcode scanning, and image-based sensing for processcontrol and security, for example, are subject to limitations imposed bythe quality of the input image. While each application will havedifferent sensitivity to the input image quality, common image qualityissues include blur, insufficient illumination, and insufficientresolution. In order to reduce blur in poorly-illuminated photographs,optical image stabilization (OIS) is an increasingly common feature ofmobile phone cameras.

High resolution image sensors are useful in consistently getting qualityimages. However, the inclusion of high resolution sensors in a cameraincreases the cost of the camera and is not always necessary for theimaging application.

Therefore, a need exists for a lower cost, flexible solution forobtaining high resolution images on demand, without the cost of a highresolution sensor.

SUMMARY

The inventors have discovered that while OIS has been developed tomitigate motion blur, the same OIS hardware can be used to produceimages with higher resolution than is provided by the image sensor,given the appropriate hardware control and image processing.

Accordingly, in one aspect, the present invention embraces a method ofproducing a high resolution image of a target with an imaging sensor(e.g., a low or lower resolution imaging sensor) associated with an OISmodule.

In an exemplary embodiment, the method is comprised of the steps of:determining, from the target size, resolution requirements of the imageto be produced; capturing multiple individual low resolution images ofthe target, (a minimum number of individual images captured being basedupon the resolution requirements determined in the determiningresolution requirements step); moving the OIS module to specificpositions between the capturing of the individual low resolution imagesin the capturing multiple low resolution images step, (the specificpositions being based upon the resolution requirements in thedetermining resolution requirements step); and processing the multiplelow resolution images to produce a high resolution image (i.e., a higherresolution image than the low (or lower) resolution images). Theprocessing step is accomplished by producing a blurred image with superresolution of the target from the captured multiple low resolutionimages; and de-blurring the blurred high resolution image to generate ahigh resolution image (i.e., a higher resolution image than the lowerresolution image).

In another exemplary embodiment of the method, the resolutionrequirements include resolution magnitude and direction.

In another exemplary embodiment of the method, the captured lowresolution images are composed of pixels. Each pixel in the de-blurredhigh resolution image has at least one corresponding pixel in the lowresolution images.

In another exemplary embodiment, the method further comprises the stepof determining a matrix for a set of linear equations which models theblurred high resolution image, based upon the step of determiningresolution limits. The de-blurring step is accomplished by applying andsolving the set of linear equations.

In another exemplary embodiment of the method, the de-blurring matrix isa Gaussian kernel.

In yet another exemplary embodiment of the method, the de-blurring stepis accomplished by the steps of: applying a Fourier transform to theblurred image with super resolution; multiplying the Fourier Transformin the frequency domain; and applying an inverse of the FourierTransform to the product of multiplying in order to generate the highresolution image.

In another exemplary embodiment of the method, the step of processingthe multiple low resolution images to produce a high resolution image isaccomplished by applying a back-projection algorithm to the multiple lowresolution images.

In another exemplary embodiment of the method, the captured lowresolution images are composed of pixels. The step of determiningresolution requirements of the image to be produced includes determiningnumber and shift locations of the OIS such that all pixels in theblurred high resolution image correspond to at least one pixel in thelow resolution images.

In another exemplary embodiment of the method, the step of applying aback-projection algorithm includes incorporating prior information onthe target in the processing to resolve ambiguities.

In yet another exemplary embodiment of the method, the step ofdetermining resolution requirements involves the steps of recognizingbarcode symbologies and determining the number of pixels in eachdirection needed for decoding.

In another exemplary embodiment, the method further comprises the stepof sending the high resolution image to decoder for decoding barcodes.

In another aspect, the present invention embraces an imaging device forproducing high resolution images of a target with an imaging sensor.

In an exemplary embodiment, the imaging device is comprised of animaging sensor, an OIS module, and a processor. The imaging sensor andthe OIS module are associated with each other. This association is notlimited to being communicatively linked, but also adapted to worktogether as discussed hereinafter. The imaging sensor and the OIS moduleare communicatively linked to the processor. In the present exemplaryembodiment, the processor is configured to determine resolutionrequirements of the image to be produced from the target size. Theprocessor is also configured to instruct the imaging sensor how many lowresolution images should be captured based upon the resolutionrequirements. The imaging sensor is configured to capture multipleimages of the target based upon the instructions from the processor. Theprocessor is further configured to determine movement of the OIS moduleto specific positions while the imaging sensor is capturing multipleimages based upon the determined resolution requirements of the imageand to communicate the determined movement to the OIS module. The OISmodule is configured to move to the specific determined positions basedupon the communications from the processor while the imaging sensor iscapturing multiple images of the target. The OIS module moves betweenthe determined positions between image captures by the imaging sensor.The processor is configured to produce a blurred image with superresolution of the target from the captured multiple low resolutionimages and is configured to de-blur the blurred high resolution image inprocessing the multiple low resolution images to produce a highresolution image.

In another exemplary embodiment, the processor is configured to usespatial domain de-blurring with a system of linear equations to processthe multiple low resolution images to produce a high resolution image.

In another exemplary embodiment, the resolution requirements includeresolution magnitude and direction.

In another exemplary embodiment, the captured low resolution images arecomposed of pixels. The number of low resolution images captured and thedetermined positions of the OIS module are sufficient, such that allpixels in the processed multiple low resolution images correspond to atleast one pixel in the captured low resolution images.

In another exemplary embodiment, the processor is configured to producea blurred image with super resolution of the target from the capturedmultiple low resolution images. The processor is also configured tode-blur the blurred high resolution image in processing the multiple lowresolution images to produce a high resolution image.

In another exemplary embodiment, the processor is configured to apply analgorithm selected from linear equations, Fourier transforms, andback-projection algorithms to the blurred image with super resolution ofthe target to de-blur the blurred high resolution image.

In yet another exemplary embodiment, the processor is further configuredto determine a matrix for a set of linear equations which models theblurred high resolution image based upon the determined resolutionrequirements.

In another exemplary embodiment, the processor is configured to apply analgorithm selected from linear equations, Fourier transforms, andback-projection algorithms to the multiple low resolution images inprocessing the multiple low resolution images to produce a highresolution image.

In yet another exemplary embodiment, the target is a barcode. Theprocessor is configured to recognize barcode symbologies whendetermining the resolution requirements. The processor is furtherconfigured to send the high resolution image to a decoder.

The foregoing illustrative summary, as well as other exemplaryobjectives and/or advantages of the invention, and the manner in whichthe same are accomplished, are further explained within the followingdetailed description and its accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 schematically depicts in a flow chart the method of producing ahigh resolution image of a target with an imaging sensor in accordancewith an exemplary embodiment of the invention.

FIG. 2 schematically depicts in a flow chart, two methods of producing ahigh resolution image from a blurred high resolution image in accordancewith the present invention.

FIG. 3 schematically shows the imaging sensor in accordance with anexemplary embodiment of the present invention.

FIG. 4 schematically shows in a flowchart the operation of the imagingsensor of FIG. 3 in accordance with an exemplary embodiment of thepresent invention.

DETAILED DESCRIPTION

The present invention embraces a method producing a high resolutionimage of a target with an imaging sensor associated with an OIS module.

In an exemplary embodiment, depicted as a flow chart in FIG. 1, themethod (100) includes the steps of: (120) determining, from the targetsize, resolution requirements of the image to be produced; (140)capturing multiple individual low resolution images of the target, aminimum number of individual images captured being based upon theresolution requirements determined in the determining resolutionrequirements step; (150) moving the OIS module to specific positionsbetween the capturing of the individual low resolution images in thecapturing multiple low resolution images step, the specific positionsbeing based upon the resolution requirements in the determiningresolution requirements step; and (160) processing the multiple lowresolution images to produce a high resolution image.

In another exemplary embodiment of the method (100), the resolutionrequirements include resolution magnitude and direction. For example, ifthe target is a barcode, the determining step (120) includes the stepsof (180) recognizing barcode symbologies, and (190) determining thenumber of pixels in each direction needed for decoding. Barcodesymbologies include, but are not limited to: UPC, EAN, Code 39, Code128, ITF (2 of 5), Code 93, CodaBar, GS1 DataBar, MSI Plessey, QR,Datamatrix, PDF417, and Aztec barcodes. In the determining step (120)for example, a UPC barcode needs more resolution in the horizontal planethan in the vertical plane. The OIS Module may have a controller and aprocessor. Alternatively, the processor may be a separate entity. Ineither case, the resolution requirements are determined, whichdetermines the number of images to be captured and the position of theOIS module for each image capture for the capturing step (140) and themoving the OIS module step (150).

In another exemplary embodiment of the method (100), the captured lowresolution images are composed of pixels; and the step (120) ofdetermining resolution requirements of the image to be produced includesthe step of (130) determining number and shift locations of the OIS suchthat all pixels in the blurred high resolution image correspond to atleast one pixel in the low resolution images. This ensures that thepixels have a one-to-one match.

In another exemplary embodiment of the method (100), the step (160) ofprocessing the multiple low resolution images may be comprised of atwo-step process (170) comprising the steps of: (172) producing ablurred image with super resolution of the target from the capturedmultiple low resolution images; and the step of (174) de-blurring theblurred high resolution image to generate a high resolution image. Asdescribed hereinbefore, the captured low resolution images are composedof pixels, and each pixel in the de-blurred high resolution image has atleast one corresponding pixel in the low resolution images.

In the case where the target is one a type of barcodes, the method alsoincludes the step (200) of sending the produced high resolution image toa decoder to decode the barcode.

In another exemplary embodiment of the method (100), there are severalprocesses possible to accomplish the step (174) of de-blurring theblurred high resolution image to generate a high resolution image.Referring to FIG. 2, in an exemplary embodiment, the step (174) ofde-blurring the blurred high resolution image to generate a highresolution image may be accomplished by the steps designatedcollectively by numeral (300). These are comprised of the steps of:(310) applying a Fourier transform to the blurred image with superresolution; (320) multiplying the Fourier Transform in the frequencydomain; and (330) applying an inverse of the Fourier Transform to theproduct of multiplying in order to generate the high resolution image.

In another exemplary embodiment, also depicted in FIG. 2, the step (174)of de-blurring the blurred high resolution image to generate a highresolution image may be accomplished by the steps designatedcollectively by numeral (400). These are comprised of the steps of:(410) determining a matrix for a linear equation which models theblurred high resolution image based upon the step (120) of determiningresolution limits; and (420) applying and solving the linear equation.In the present embodiment, for example, the matrix or the de-blurringmatrix is a Gaussian kernel.

In general, the step (160) of processing the multiple low resolutionimages to produce a high resolution image may be accomplished byapplying an algorithm to the multiple low resolution images. Thecollective steps (170), (300) and (400) previously described illustrateparticular embodiments of this. In general, the algorithm selected isnot limited to these, but may include linear equations, Fouriertransforms and back projection algorithms and the like.

In an exemplary embodiment, applying a back-projection algorithm wouldentail incorporating prior information on the target in the processingstep (160) to resolve ambiguities.

The present invention also embraces an imaging device for producing highresolution images of a target with an imaging sensor.

Referring now to FIG. 3, in an exemplary embodiment, the imaging device(500) is comprised of: an imaging sensor (510) (e.g., a low or lowerresolution imaging sensor), an OIS module (520), and a processor (530).The processor (530) is communicatively linked to the OIS module (520)and the imaging sensor (510), as designated by the connecting arrows.The imaging sensor (510) is associated with the OIS module (520) asdesignated by the connecting dotted line arrow. This association is aspatial relationship, not electrical; the OIS is in the optical path ofphotons which reach the imaging sensor.

OIS modules, as is known in the art, generally include an OIScontroller. Generally, as is known in the art, OIS modules work in theconventional manner of either moving the lens or system of lenses ormove the image sensor itself to correct for image device shaking. Eithertype of OIS module will work in the present invention.

In the present invention, the imaging sensor (510) is associated withthe OIS module (520) in that the imaging sensor (510) and the OIS module(520) can be made to work together via the processor (530) for theinventive application of the present invention.

In another exemplary embodiment, the processor (530) may be part of theOIS module (520) although in the present Figure they are shown asseparate entities.

In the case, as shown, where the target (10) is a barcode, the imagingsensor (500) may include or have access to a barcode decoder (540).

Referring now to FIG. 4, the operation of the imaging device (500) ofFIG. 3 in producing a high resolution image of a target (10) is shown ina flowchart. The operation is generally designated (600). In operation,the first step is (610) the imaging sensor “sees” a target. Then (620)the processor determines from the target type and size the resolutionrequirements, including the magnitude and direction of the resolutionrequirements. For example, as shown in FIG. 3, the target (10) is a UPCbarcode. Higher resolution is needed in the horizontal dimension than inthe vertical dimension for a UPC. However, if the target is a QR code(not shown), both dimensions need the same resolution. Next (630) theprocessor instructs the imaging sensor how many images to capture, basedon the resolution requirements. For example, the higher the resolutionrequirements, the more images the processor will instruct the imagingsensor to capture. Also (640) the processor determines the movement ofthe OIS module to specific positions during the image capture sequence.These positions are based also on the resolution requirements for eachdimension. For example, if the target is a UPC code, the OIS module maybe instructed to move to several positions in the horizontal dimensionduring the image capture, but not move with respect to the verticaldimension. Note that the OIS module moves to a new position betweenimage captures. Then (650) the imaging sensor captures multiple imagesof the target based on the number instructed by the processor. (660) TheOIS module moves to the specific positions as described hereinabove. In(670) the processor produces a blurred image with super resolution fromthe captured multiple low resolution images. Finally, (680) theprocessor de-blurs the blurred high resolution image to produce a highresolution image.

Continuing to refer to FIG. 4, as stated above, in processing themultiple low resolution images, (670) the processor produces a blurredimage with super resolution of the target from the captured multiple lowresolution images. (680) The processor de-blurs the blurred highresolution image. In an exemplary embodiment (700) The processor usesspatial domain de-blurring with a system or matrix of linear equationsto produce a high resolution image. The system of linear equations mayinclude algorithms such as Fourier transforms, and linear equationmatrices.

In another exemplary embodiment (not shown), the processor is configuredto use a back projection algorithm, which incorporates prior informationabout the target in the processing to resolve ambiguities in order toproduce the high resolution images. This can be done in conjunction withthe de-blurring techniques described hereinbefore to resolve ambiguities

In the event that the target (10) is a barcode, as shown, the processoris also configured in (690) to send the high resolution image to abarcode decoder for decoding the barcode.

It is to be understood, that the present invention uses multiple imagesto increase the spatial resolution, which sacrifices temporalresolution, that is, it takes longer to produce a high resolution imageusing the present invention. However, the present invention allows bothhigh and low resolution images to be produced with inexpensive equipmenton demand, that is, not every image produced has to be high resolution.The same hardware that is incorporated in many imaging devices such assmart phones and cameras can be used by controlling the hardware in anovel way as described hereinbefore, and through image processing asdescribed hereinbefore.

To supplement the present disclosure, this application incorporatesentirely by reference the following commonly assigned patents, patentapplication publications, and patent applications:

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In the specification and/or figures, typical embodiments of theinvention have been disclosed. The present invention is not limited tosuch exemplary embodiments. The use of the term “and/or” includes anyand all combinations of one or more of the associated listed items. Thefigures are schematic representations and so are not necessarily drawnto scale. Unless otherwise noted, specific terms have been used in ageneric and descriptive sense and not for purposes of limitation.

1. A method, comprising: determining, from a target size, resolutionrequirements of an image to be produced; capturing multiple individuallower resolution images of a target, a number of individual imagescaptured being based upon the determined resolution requirements; movingan OIS module to specific positions between the capturing of theindividual lower resolution images, the specific positions being basedupon the determined resolution requirements; and processing the multiplelower resolution images to produce a higher resolution image.
 2. Themethod of claim 1, wherein the resolution requirements includeresolution magnitude and direction.
 3. The method of claim 1, whereinthe captured lower resolution images are composed of pixels, and whereineach pixel in the de-blurred higher resolution image has at least onecorresponding pixel in the lower resolution images.
 4. The method ofclaim 1, further comprising the step of determining a matrix for a setof linear equations which models the blurred higher resolution imagebased upon the step of determining resolution limits and wherein thede-blurring step is accomplished by applying and solving the set oflinear equations.
 5. The method of claim 4, wherein the de-blurringmatrix is a Gaussian kernel.
 6. The method of claim 1, wherein thede-blurring step is accomplished by the steps of: applying a Fouriertransform to the blurred image with super resolution; multiplying theFourier Transform in the frequency domain; and applying an inverse ofthe Fourier Transform to the product of multiplying in order to generatethe higher resolution image.
 7. The method of claim 1, wherein the stepof processing the multiple lower resolution images to produce a higherresolution image is accomplished by applying a back projection algorithmto the multiple lower resolution images.
 8. The method of claim 1,wherein the captured lower resolution images are composed of pixels; andthe step of determining resolution requirements of the image to beproduced includes determining number and shift locations of the OIS suchthat all pixels in the blurred higher resolution image correspond to atleast one pixel in the lower resolution images.
 9. The method of claim7, wherein the step of applying a back-projection algorithm includesincorporating prior information on the target in the processing toresolve ambiguities.
 10. The method of claim 1, wherein the step ofdetermining resolution requirements involves the steps of: recognizingbarcode symbologies and determining the number of pixels in eachdirection needed for decoding.
 11. The method of claim 10, furthercomprising the step of sending the higher resolution image to a decoder.12. A device, comprising: an imaging sensor; an optical imagestabilization (OIS) module, the imaging sensor and the OIS module beingassociated; and a processor communicatively linked to the OIS module andthe imaging sensor; the processor being configured to: determineresolution requirements of an image to be produced from a target size;instruct the imaging sensor how many lower resolution images should becaptured based upon the resolution requirements; capture multiple imagesof the target based upon the instructions from the processor; determinemovement of the OIS module to specific positions while the imagingsensor is capturing multiple images based upon the determined resolutionrequirements of the image and to communicate the determined movement tothe OIS module; the OIS module being configured to move to the specificdetermined positions based upon the communications from the processorwhile the imaging sensor is capturing multiple images of the target, theOIS module moving between the determined positions between imagecaptures by the imaging sensor; and the processor is configured toprocess the multiple lower resolution images to produce a higherresolution image.
 13. The device of claim 12, wherein the processor isconfigured to use spatial domain de-blurring with a system of linearequations to process the multiple lower resolution images to produce ahigher resolution image.
 14. The device of claim 12, wherein theresolution requirements include resolution magnitude and direction. 15.The device of claim 12, wherein the captured lower resolution images arecomposed of pixels; and wherein the number of lower resolution imagescaptured and the determined positions of the OIS module are sufficientsuch that all pixels in the processed multiple lower resolution imagescorrespond to at least one pixel in the captured lower resolutionimages.
 16. The device of claim 12, the processor is configured to applyan algorithm selected from linear equations, Fourier transforms, andback-projection algorithms to the blurred image with super resolution ofthe target in de-blurring the blurred higher resolution image.
 17. Thedevice of claim 16, wherein the processor is further configured todetermine a matrix for a set of linear equations which models theblurred higher resolution image based upon the determined resolutionrequirements.
 18. The device of claim 12, wherein the processor isconfigured to apply an algorithm selected from linear equations, Fouriertransforms, and back-projection algorithms to the multiple lowerresolution images in processing the multiple lower resolution images toproduce a higher resolution image.
 19. The device of claim 12, whereinthe target is a barcode; wherein the processor is configured torecognize barcode symbologies when determining the resolutionrequirements; and wherein the processor is configured to send the higherresolution image to a decoder.